Analog Allpass Filters
It turns out that analog allpass filters are considerably simpler
mathematically than digital allpass filters (discussed in
§B.2). In fact, when working with digital allpass filters,
it can be fruitful to convert to the analog case using the bilinear
transform (§I.3.1), so that the filter may be manipulated in the
analog plane rather than the digital
plane. The analog case
is simpler because analog allpass filters may be described as having a
zero at
for every pole at
, while digital allpass
filters must have a zero at
for every pole at
.
In particular, the transfer function of every first-order analog
allpass filter can be written as







This simplified rule works because every complex pole


![$ k\in[1:N]$](http://www.dsprelated.com/josimages_new/filters/img1918.png)
Multiplying out the terms in Eq.(E.14), we find that the numerator
polynomial
is simply related to the denominator polynomial
:








As an example of the greater simplicity of analog allpass filters
relative to the discrete-time case, the graphical method for computing
phase response from poles and zeros (§8.3) gives immediately
that the phase response of every real analog allpass filter is equal
to twice the phase response of its numerator (plus when
the frequency response is negative at dc). This is because the angle
of a vector from a pole at
to the point
along the
frequency axis is
minus the angle of the vector from a zero at
to the point
.
Lossless Analog Filters
As discussed in §B.2, the an allpass filter can be defined
as any filter that preserves signal energy for every input
signal . In the continuous-time case, this means


















where denotes the Dirac ``delta function'' or continuous
impulse function (§E.4.3). Thus, the allpass condition becomes

Suppose






(We have normalized so that
is monic (
) without
loss of generality.) Equation (E.15) implies








and
, in which case
for all
.
-
and
, i.e.,
By analytic continuation, we have











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Quality Factor (Q)